Meta-analysis of methods to change implicit bias Patrick S. Forscher

What interventions are available? Implicit bias has been argued to contribute to a variety of social problems Many people have issued calls for effective interventions to change implicit bias What interventions are available? How well do they work?

Study inclusion criteria Must include measure of implicit bias Also coded correspondent explicit, behavioral measures The implicit measure must be a pre-existing tendency positive scores = pre-existing tendency Reported in English Must have sufficient information to calculate effect sizes Must be randomized The study must have at least two unique conditions according to the coding scheme Point 1: Mention that prevailing assumption is that if you change implicit, you’ll change behavior Point 6: Mention that this means we can’t handle studies that compare two different methods of perspective taking

Searched PsychINFO, Web of Science, and ProQuest (implicit measure title or acronym) AND (malleab* OR chang* OR influenc* OR moderat* OR reduc* OR increas* OR shift* OR alter*) AND (1995 TO 2013)

341 articles, 489 studies, 552 samples Searched PsychINFO, Web of Science, and ProQuest Completed manual searches through Google Scholar Requested papers directly through direct email and SPSP listserv 3607 articles Completed more detailed check against inclusion criteria 341 articles, 489 studies, 552 samples Requested additional data for 301 incomplete samples 273 articles (223 published, 50 unpublished) 395 studies, 442 samples 44,946 participants

Group coding categories Pair incongruent/Pair congruent Famous actor who played the lead role in “Remember the Titans” Boxer who bit an opponent’s ears during a fight Mention that coding scheme is attempting to classify procedures rather than the goals of the researchers Serial killer who cannibalized his victims Famous actor who played the lead role in “Apollo 13”

Group coding categories Pair incongruent/Pair congruent Pair incongruent (indirect)/Pair congruent (indirect) Perspective taking

Group coding categories Direct instructions to exhibit Pair incongruent/Pair congruent Pair incongruent (indirect)/Pair congruent (indirect) Incongruent goal/Congruent goal Direct instructions to exhibit a certain response

Group coding categories Pair incongruent/Pair congruent Pair incongruent (indirect)/Pair congruent (indirect) Incongruent goal/Congruent goal Threat

Group coding categories Considering one’s values Pair incongruent/Pair congruent Pair incongruent (indirect)/Pair congruent (indirect) Incongruent goal/Congruent goal Threat Affirmation Considering one’s values

Group coding categories Completing a cognitively taxing task Pair incongruent/Pair congruent Pair incongruent (indirect)/Pair congruent (indirect) Incongruent goal/Congruent goal Threat Affirmation Positive mood/Negative mood Depletion Completing a cognitively taxing task

Participant characteristics 88% student, 12% non-student 49% female, 27% male, 25% not reported 39% White, 9% non-White, 51% not reported Measure characteristics 59% attitudes, 20% cognition, 8% self-esteem, 12% self-concept 67% IAT, 11% semantic priming, 5% LDT, 17% other 5% longitudinal Demographic characteristics of intro psych students Study characteristics 56% US, 27% Europe, 17% other 62% prejudice/stereotyping, 24% health/clinical, 15% self, 9% other 49% two groups, 21% three groups, 30% four+

Participant characteristics 88% student, 12% non-student 49% female, 27% male, 25% not reported 39% White, 9% non-White, 51% not reported Measure characteristics 59% attitudes, 20% cognition, 8% self-esteem, 12% self-concept 67% IAT, 11% semantic priming, 5% LDT, 17% other 5% longitudinal Participant characteristics reflect demographics of introductory psychology students. Wide variety of measures, but most studies use the IAT. Very few longitudinal studies. Multi-group studies are important because they mean that conventional methods of meta-analysis are not possible Study characteristics 56% US, 27% Europe, 17% other 62% prejudice/stereotyping, 24% health/clinical, 15% self, 9% other 49% two groups, 21% three groups, 30% four+

Network meta-analysis d = -.56 𝑑= 𝑥1 −𝑥2 𝑠𝑝

Network meta-analysis d = -.56 Network meta-analysis handles multi-group studies, outcome is standardized mean difference, must choose a common reference group. There are a few more subtleties for those who are interested d = .42 𝑑= 𝑥1 −𝑥2 𝑠𝑝

Assessing the network of interventions

Results: Implicit data

Indirect pairings are not symmetric, and neither are the goals manipulations.

Results: Moderators

Most of the IAT effect sizes are larger than the non-IAT effect sizes

Domain seems to matter for pair incongruent (indirect) and threat

Results: Behavioral data I could add the explicit analyses here too, but I thought there might not be enough time

Here I point out that this network looks very different from the implicit network. In particular, most interventions are only connected to the neutral control group and their conceptual opposite.

Meta-analytic implicit-behavioral correlation: r = .086, [.047, .12], k = 46

Meta-analytic implicit-behavioral correlation: r = .086, [.047, .12], k = 46

Provisional conclusions Implicit bias is malleable Methodological caveats: Most of our data come from students We do not know if the effects endure How effective a manipulation appears to be depends on the implicit measure used Conceptual caveats: The effectiveness of a manipulation depends on the content domain Effects on implicit bias do not necessarily generalize to behavior

Collaborators Trish Devine Calvin Lai Michelle Herman Jordan Axt Feel free to swap out any of these pictures for different ones if desired Michelle Herman Jordan Axt Brian Nosek Charlie Ebersole